This invention relates to near infrared spectrographic analysis, and more particularly to an improved system and method of spectroanalysis wherein reflection or transmission of samples are measured at remote sites and are transmitted to a central location for analysis.
Near infrared (NIR) spectrographic instruments are used to provide accurate analysis of materials such as to determine measurable characteristics of the materials. For example, concentrations of constituents of the materials or alternatively physical characteristics of the materials may be measured. In agriculture near infrared spectrographic instruments are used to determine the oil, protein, and moisture content of grain, the fat content of meat, the fat, protein and lactose content of milk, and urea content of milk. In addition, the instruments are used to analyze blood samples, pharmaceutical and synthetic resins.
In typical systems of the prior art, a measurable characteristic is expected to correlate with absorbance at selected wavelengths in the near infrared spectrum. The measurable characteristics of a material can be represented in an equation summing products of weighting coefficients and values from the absorbance spectrum of the material or by an equation summing products of weighting coefficients and values from a derivative of the absorbance spectrum. Typically, a first order derivative of the absorbance spectrum is used, but higher order derivatives may also be used. Collectively, the undifferentiated absorbance spectra and the derivatives of the absorbance spectra are all called absorbance spectra. To measure the concentrations of constituents of an unknown sample or measure physical characteristics of the unknown sample, the absorbances of a multiplicity of known sample materials similar to the unknown material are measured by the spectrographic instrument. The concentrations or the characteristics to be measured in the known sample materials are known. From the absorbance measurements made on the multiplicity of known sample materials, the weighting coefficients of the equations relating the measurable characteristics to the absorbance measurements are determined by multiple regression, by partial least squares of regression or other statistical techniques. The process of determining the values of the weighting coefficients is called calibration. After the coefficients have been determined, the unknown material can be analyzed by the spectrographic instrument using the coefficients that have been determined from the known sample materials. Typically in modern instruments instead of measuring the absorbances at selected specific wavelengths which are known or presumed to correlate with the measurable characteristics, the absorbances of the sample are measured at wavelengths distributed throughout the near infrared spectrum and coefficients and equations relating the measurable characteristics to the absorbance measurements throughout the spectrum are developed by partial least squares, or other statistical technique. The measurable characteristics of the unknown material are then determined by the spectrographic instrument measuring the absorbances of the unknown material and then calculating the measurable characteristics from the measured absorbance values in accordance with the equations. To perform the analysis, the spectrographic instrument is typically provided with a data processor and special software to carry out the analysis. Spectrographic instruments capable of performing material analysis are expensive and a large part of the cost of a spectroanalysis instrument is in the data processor, provided with the necessary software, required to carry out the spectroanalysis. In addition, using the instruments to make the measurements is a relatively complex process, and users of the instruments have to be specially trained. Also the users of the instruments typically require ongoing support to enable the users to consistently make accurate measurements. Because of the relatively high cost of spectroanalysis instruments, the requirements for users of the instruments to be trained, and the requirement for ongoing support, there is a need to reduce the expense and complexity of NIR spectroanalysis of materials.
In accordance with the present invention, the cost of spectrographic analysis is greatly reduced by eliminating the need for the costly data processors at each spectrographic instrument. In addition, the measurement process is substantially simplified from the user""s point of view and the need for special training and ongoing support is eliminated. In accordance with the invention, each spectrographic instrument is provided with the spectrographic hardware to make reflection and/or transmission measurements on sample materials. Each spectrographic instrument site is provided with a simple data processor to receive the spectrographic measurements, convert them to absorbance measurements, and transmit the absorbance measurements to a central site by means of the Internet. At the central location, the spectral data is analyzed to provide the desired measurements on the sample material from which the spectral data were measured.
In order to accurately analyze the spectral data at the central site location, the spectral data must first be standardized so that the spectral data received from any remote location, each having its own spectrographic instrument, is the same as if the spectra obtained from each sample had been measured by the same spectrographic instrument. For this purpose, the central location stores standardization files, one for each remotely located spectrographic instrument of the system. The standardization file for each instrument is generated by comparing absorbance spectra measured by the remote instrument from a standard sample with the absorbance spectra obtained from the standard sample by a master spectrographic instrument. By means of this standardization file the data in the spectra received from the remote sample can be modified to be the same as if it had been measured by the master instrument.
The central location also stores a library of spectra for a large number of different samples, the composition or other measurable characteristics of which are known. The spectra obtained from the unknown sample is compared with the library spectra to determine by a mathematical process weighting coefficients of functions relating absorbance values to the characteristics being measured. In the preferred embodiment the spectrum from the unknown sample is first compared by correlation with the spectra from the known samples in the library to find a set of spectra which closely correlate with the spectra from the unknown sample. For example, 100 spectra in the library which most closely correlate with the unknown sample may be selected. The selected spectra from the library are then used to generate a set of weighting coefficients for the unknown sample. Alternatively the unknown spectrum can be compared with the entire library of spectra using neural networks to determine the weighting coefficients of neural network functions. The coefficients are multiplied times the absorbance values in the spectrum from the unknown sample to provide an analysis of the sample.
The analysis of the unknown sample may then be transmitted electronically to the user at the remote site. The spectra of the unknown sample may be added to the library of spectra at the central site along with the characteristics of the unknown material determined by conventional laboratory methods.
By having the analysis performed at a central site, the need for training personnel to use the instrument, the ongoing support of such personal, and the need for a costly computer at each remote site are eliminated. In addition, advantageous use may be made of a large library of spectra at the central site without having to duplicate this library at each remote location. As a result, spectroanalysis is substantially greatly simplified for users and its cost is substantially reduced.